Back to Search
Start Over
Wavelet-Based Image Texture Classification Using Local Energy Histograms.
- Source :
- IEEE Signal Processing Letters; Apr2011, Vol. 18 Issue 4, p247-250, 4p
- Publication Year :
- 2011
-
Abstract
- In this letter, we propose an efficient one-nearest-neighbor classifier of texture via the contrast of local energy histograms of all the wavelet subbands between an input texture patch and each sample texture patch in a given training set. In particular, the contrast is realized with a discrepancy measure which is just a sum of symmetrized Kullback–Leibler divergences between the input and sample local energy histograms on all the wavelet subbands. It is demonstrated by various experiments that our proposed method obtains a satisfactory texture classification accuracy in comparison with several current state-of-the-art texture classification approaches. [ABSTRACT FROM PUBLISHER]
Details
- Language :
- English
- ISSN :
- 10709908
- Volume :
- 18
- Issue :
- 4
- Database :
- Complementary Index
- Journal :
- IEEE Signal Processing Letters
- Publication Type :
- Academic Journal
- Accession number :
- 62558588
- Full Text :
- https://doi.org/10.1109/LSP.2011.2111369